Khái niệm cốt lõi
Proposing a multimodal deep learning model for affect status forecasting by integrating wearable sensor data and self-reported diaries.
Thống kê
Our results demonstrate that the proposed model achieves predictive accuracy of 82.50% for positive affect and 82.76% for negative affect, a full week in advance.
Trích dẫn
"The proposed model exhibits satisfactory accuracy for forecasting affect status."
"Our results stress the importance of personalized methods in monitoring mental health."